Abstract
Systemic anticancer immunity can be reinstated via the induction of immunogenic cell death (ICD) in malignant cells. Thus, certain classes of cytotoxic compounds, for example, anthracyclines, oxaliplatin and taxanes are endowed with the capacity to act on cancer cells to ignite premortem stress pathways that lead to the surface exposure of calreticulin (CALR) and the cellular release of adenosine triphosphate, annexin A1, high mobility group B1 and type-1 interferons. Altogether, these alterations constitute the hallmarks of ICD. Here we report the design of a discovery pipeline for the identification of novel ICD inducers by means of a phenotypic screening platform. The use of fluorescent biosensors as proxies for the manifestation of ICD hallmarks has enabled the exploration of large collections of chemical compounds by automatized screening routines. Imaging-based assessment and phenotypic selection led to the identification of potential ICD inducers that could be validated further invitro and invivo, confirming that bona fide ICD inducers possess the capacity to induce immunological long-term memory and to confer resistance against rechallenge with syngeneic tumors. Machine learning algorithms analyzing the physicochemical properties of ICD inducers can assist in the preselection of compounds with potential ICD-stimulatory properties, further accelerating the screening efforts designed to develop new immunotherapeutic agents.